def step_les_models(model_time, work_queue, offset=les_spinup):
global errorFlag
les_wall_times = []
if not any(les_models):
return les_wall_times
if les_queue_threads >= len(
les_models): # Step all dales models in parallel
if async_evolve: # evolve all dales models with asynchronous Amuse calls
reqs = []
pool = AsyncRequestsPool()
for les in les_models:
req = les.evolve_model. async (model_time + (offset | units.s),
exactEnd=True)
reqs.append(req)
pool.add_request(req)
# now while the dales threads are working, sync the netcdf to disk
spio.sync_root()
# wait for all threads
pool.waitall()
try:
les_wall_times = [r.result().value_in(units.s) for r in reqs]
log.info("async step_les_models() done. Elapsed times:" +
str(['%5.1f' % t for t in les_wall_times]))
except Exception as e:
log.error("Exception caught while gathering results: %s" %
e.message)
else: # evolve all dales models using python threads
threads = []
for les in les_models:
t = threading.Thread(target=step_les,
args=(les, model_time, offset),
name=str(les.grid_index))
# t.setDaemon(True)
threads.append(t)
t.start()
# now while the dales threads are working, sync the netcdf to disk
spio.sync_root()
# wait for all threads
for t in threads:
# log.info("Waiting to join thread %s..." % t.name)
t.join()
# log.info("joined thread %s" % t.name)
elif les_queue_threads > 1:
for les in les_models:
work_queue.put((les, model_time)) # enqueue all dales instances
# now while the dales threads are working, sync the netcdf to disk
spio.sync_root()
work_queue.join() # wait for all dales work to be completed
if errorFlag:
log.info("One thread failed - exiting ...")
# stop_worker_threads(work_queue) # signal worker threads to quit - now an atexit function, should not
# need it here
finalize()
sys.exit(1)
else: # sequential version
for les in les_models:
step_les(les, model_time, offset)
return les_wall_times
